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• Research on CV, LLM for scalable business solutions: 2D/3D data synthesis…
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Virginia Tech
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Researching on Computer Vision, Machine Learning, Deep Learning, Data Science, Artificial Intelligence and Robotics
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Sudarshan Lamkhede
The BayLearn 2024 abstract submission deadline has been extended to Aug 5, 2024. If you are working on cutting-edge ML research, please consider submitting an abstract. BayLearn 2024 will be an in-person event, held on Oct 10, 2024: https://baylearn.org This is a great opportunity for student researchers to showcase their latest research work and get good feedback. Submissions are non-archival and the review process is quite informal. #machinelearning #research
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Jordan Sarasan
New book alert! "Image Processing Recipes in MATLAB" is a comprehensive collection of 30 practical recipes for image processing, covering foundational techniques to the latest algorithms. 🖥️ Tailored for ease of use, it provides clear, step-by-step instructions and visual examples, complete with source code for each recipe, making it a practical guide for implementing efficient image processing workflows in #MATLAB. 🚀 #ImageProcessing https://spr.ly/6047gt5dF
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Alexander Helm
The 1st deadline for the NVIDIA Academic Grant program is in 1 week. We're accepting proposals for #GenAI #LLMs and Simulation & Modeling. You mustbe a full-time faculty member at an accredited academic institution that awards research degrees to PhD students. NVIDIA will be funding proposals for innovative work related to generative AI and large language models (LLMs), including multi-modal models and content generation, such as diffusion models. Projects should incorporate pretrained models from ai.nvidia.com or use NIMs, Modulus, TensorRT(-LLM), NeMo, NeMo Retriever, NeMo Data Curator, BioNemo, NeMo Guardrails, or Isaac Sim/Lab. Gen AI & LLM Proposals should be attached to one of more of the following themes: Techniques for Training, Customizing, and Accelerating GenAI Exploring New Approaches and Architectures for LLMs and GenAI or Foundational Models and Scientific Applications Using GenAI Simulation Proposals should be attached to one of more of the following themes: Simulation and modeling that incorporate Modulus, Omniverse, HPC SDK, cuNumeric, cuQuantum, or CUDA Quantum. Proposals should be attached to one of more of the following themes: Computational Fluid Dynamics Physics-Informed Machine Learning Quantum Computing Scientific Simulation Selected Principal Investigators (PIs) may receive Up to 32,000 A100 40GB hours or equivalent OR up to 8 RTX 6000 Ada
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